def test_enable_eager_for_tf_1(self, mock_eager_execution, mock_is_tf_v1):
mock_is_tf_v1.return_value = False
utils.enable_eager_for_tf_1()
# Work around as assert_not_called is not supported in py35
self.assertFalse(mock_eager_execution.called)
mock_is_tf_v1.return_value = True
utils.enable_eager_for_tf_1()
mock_eager_execution.assert_called_once_with()
# See the License for the specific language governing permissions and
# limitations under the License.
"""End to end integration test for cloud_fit."""
import os
from typing import Text
import uuid
from absl import logging
import numpy as np
import tensorflow as tf
from tensorflow_cloud.tuner import cloud_fit_client as client
from tensorflow_cloud.tuner import cloud_fit_utils as utils
from tensorflow_cloud.utils import google_api_client
# Can only export Datasets which were created executing eagerly
utils.enable_eager_for_tf_1()
MIRRORED_STRATEGY_NAME = utils.MIRRORED_STRATEGY_NAME
MULTI_WORKER_MIRRORED_STRATEGY_NAME = utils.MULTI_WORKER_MIRRORED_STRATEGY_NAME
# The staging bucket to use to copy the model and data for remote run.
_REMOTE_DIR = os.path.join("gs://", os.environ["TEST_BUCKET"])
# The project id to use to run tests.
_PROJECT_ID = os.environ["PROJECT_ID"]
# The GCP region in which the end-to-end test is run.
_REGION = os.environ["REGION"]
# The base docker image to use for remote environment.
_DOCKER_IMAGE = os.environ["DOCKER_IMAGE"]